Been working on https://localhero.ai, its my service to automate on-brand translations for product teams. I've been doing outreach to Swedish companies/people, getting some good interest from a few that want to automate their localization workflow but don't want the work of maintaining own solutions. Even though you can build a version working with coding agents these days, there is a lot of stuff around it to make it work well over time in a product org. On the tech side for Localhero, one thing I've been working on how it learns from manual edits. Like when a PM or designer tweaks copy in the Localhero UI, those things now better feed back into a translation memory and influence future translations. It's like a self-learning loop, turns out a pretty nice combo of using old-school techniques and offloading some work to LLMs.

Also been spending some time on my old side project https://infrabase.ai, an directory of AI infra related tools. Redesigned the landscape page (https://infrabase.ai/landscape), going through product submissions and content, optimizing a bit for seo/geo.

Building https://localhero.ai, automated on-brand i18n translations that run in your CI pipeline. Right now I'm working on better .po/gettext support, based on feedback from an early customer. With gettext you usually keeps source strings in the actual source code. So I'm building a workflow where non-technical people (PMs, designers) can edit translations in the web UI and then easily generate a PR with both code changes and translation file updates. Trying to make translations work smooth for both automated CI pipelines and PMs/designers who don't live in Git, when translations are checked into the repo. Also going through my network, talking to devs and localization folks to understand what could be improved in their orgs for translations.

Nice! We use an internal workflow with translations by llms at Minut. This looks smoother, esp as everything is driven through the PR. Swapped out lokalize for cost reasons.

Edit: we’re Malmö-based, lmk if you want to chat.

Cool, I'll drop a dm on linkedin!

Building https://localhero.ai, automated on-brand i18n translations that run in your CI pipeline.

Right now I'm working on better .po/gettext support, based on feedback from an early customer. With gettext you usually keeps source strings in the actual source code. So I'm building a workflow where non-technical people (PMs, designers) can edit translations in the web UI and then easily generate a PR with both code changes and translation file updates. Trying to make translations work smooth for both automated CI pipelines and PMs/designers who don't live in Git, when translations are checked into the repo. Also going through my network, talking to devs and localization folks to understand what could be improved in their orgs for translations.

I'm building https://localhero.ai. Automated i18n translations that run in your CI pipeline.

I have worked as dev in many different constellations of the years, and seen many teams choose between bad options like delay feature launches for manual translations, ship incomplete translations and promise "we'll translate it later," or lately use ChatGPT/LLMs that lose consistency/context and require coordination.

Localhero starts from the premise that translations are part of CI. New strings get translated automatically in GitHub Actions, with glossaries and style guides so it sounds like your product and not generic AI output.

Goal is to help product teams ship localized features without all the coordination/delay.